Global $q$-dependent inverse transforms of intensity autocorrelation data

TL;DR

This paper introduces a novel nonlinear modeling approach for analyzing intensity autocorrelation data from dynamic light scattering and X-ray photon correlation spectroscopy, allowing for detailed decomposition of complex dynamics without prior scaling assumptions.

Contribution

It generalizes existing methods by directly modeling the $g_2$ function, providing a flexible and open-source tool for analyzing complex soft matter dynamics.

Findings

Successfully decomposed soft matter dynamics into diffusion rate distributions

Enhanced analysis flexibility over traditional methods

Open-source MATLAB implementation available

Abstract

We present a new analysis approach for intensity autocorrelation data, as measured with dynamic light scattering and X-ray photon correlation spectroscopy. Our analysis generalizes the established CONTIN and MULTIQ methods by direct nonlinear modeling of the $g_2$ function, enabling decomposition of complex dynamics without a priori knowledge of experimental scaling factors. We describe the mathematical formulation, implementation details, and strategies for solution, as well as demonstrate decompositions of soft matter dynamics data into distributions of diffusion rates/velocities. The open-source MATLAB implementation, including example data, is publicly available for adoption and further development.